Security in Internet of Vehicles (IoV)
Internet of Vehicles (IoV) has been a growing technology since the invention of
smart vehicles that contain connected sensors and electronic control units (ECU).
These devices reinforce the long-awaited goal of autonomous driving [1]. At the
same time, wireless communication has paved the way for faster data transfer,
more reliability, lower latency, and availability. These improvements in wireless
communication are adopted by different protocols and applications in IoV [2]. In
general terms, IoV is the amalgamation of Vehicular Ad Hoc Networks (VANET)
with Internet of Things (IoT) [3]. Nowadays, connected vehicles leverage IoT to
connect to networks and benefit from real-time traffic information, navigation,
and other driving facility features. According to Gartner, 5G IoT will be the
pioneer communication technology for connected cars. Gartner also states that
by 2030, a large proportion of market opportunity for 5G IoT will be devoted to
the automotive industry as connected cars will occupy around 53% of the overall
5G IoT endpoints [4].
IoV takes advantage of many networking technologies to provide connectivity
between various units inside the vehicle as well as communication between
different road entities (e.g., other vehicles and roadside infrastructure) to benefit
from intelligent knowledge sharing. However, connectivity through the network
always carries its risks especially since the IoV network contains several IoT
sensors and processors. Moreover, ongoing communication between road entities
alongside the network, makes IoV an open target to intruders [5]. IoV security is
a serious issue as it may cause human fatality if erroneous information interferes
with the vehicles’ decision-making. Attackers can exploit the vulnerabilities in
networking communication and perform malicious activities such as taking the
car’s control, broadcasting misleading information in the network, or other
attacks that can endanger the confidentiality, integrity, and availability of the
vehicle system, as well as the authenticity of users. For example, an attack
performed by a group of hackers was able to trick Tesla’s Autopilot self-driving
software into swerving into an oncoming traffic lane [6]. Moreover, autonomous
driving provides a huge amount of data, which is utilized for Artificial
Intelligence (AI) enabled applications and data mining purposes. Users’ data
privacy could be at risk due to the sensitivity of the data shared among the users.
